Academic Information

RBIF 111

R for Biomedical Informatics

This course is an advanced mathematics and applied statistics course that will introduce students to data analysis methods and statistical testing. It provides a foundation for Biological Data Mining and Modeling (RBIF 112) and Design and Analysis of Microarray Experiments (RBIF114). The course covers R (a statistical programming language) to introduce students to descriptive and inferential statistics, basics of programming, common data structures and analysis techniques. The course covers methods important to data analysis such as t-tests, chi-squared analysis, Mann-Whitney tests, correlation and regression, ANOVA, LDA, PCA, tests of significance, and Fisher's exact test.

At the end of the course, students will be able to:

Write programs in R for data analysis.

Discern appropriate data models to answer specific questions.

Analyze data with a number of statistical models.

Conduct explorative analysis of large data sets.

Choose appropriate methods of analysis for a given problem.

Perform tests to validate models against data.

Evaluate various statistical methods on the basis of their strengths and weaknesses.

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Brandeis combines the breadth and scope of a world-class research university with the intimacy and accessibility of a small liberal arts college. Consistently ranked among the nation’s best universities, Brandeis is widely recognized for the excellence of its teaching, the quality and diversity of its student body and the outstanding research of its faculty.As a leading research university and member of the prestigious Association of American Universities, Brandeis fosters self-motivated, curious students ready to engage new experiences and equipped for global endeavors.